The Data Analyst will be responsible for collecting, processing, and analysing data to provide actionable insights that support decision-making across the organisation. This role involves working closely with various stakeholders to understand their data needs and delivering high-quality reports and visualisations.
Key Responsibilities:
- Data Collection and Management:
Gather data from various sources, ensuring accuracy and consistency.Support Data Engineers to maintain and manage databases, ensuring data integrity and security. - Data Analysis:
Conduct exploratory data analysis to identify trends, patterns, and anomalies. Apply statistical techniques and models to interpret data and generate insights. - Reporting and Visualisation: Create comprehensive reports and dashboards to communicate findings to stakeholders. Develop visualisations using tools such as Tableau, Power BI, or Excel to present complex data in an understandable manner.
- Data Modelling and Transformation:
Define data‑model attributes for loan and trading book assets, portfolio holdings, collateral data, client data, GL data, credit risk attributes, etc.Understand Moody's Risk Authority data feeds for RWA, ICAAP and CoRep feeds for regulatory reporting. - Collaboration with Stakeholders:
Work closely with business units to understand their data requirements and provide analytical support. Write user stories with quantifiable acceptance criteria.Communicate findings and recommendations clearly to both technical and non-technical stakeholders. - Quality Assurance:Ensure the accuracy and reliability of data through validation and quality control processes.Identify and address data quality issues proactively. Run UAT, including parallel‑run comparisons with legacy warehouse.
- Continuous Improvement:
Stay updated on industry trends, tools, and best practices in data analysis. Suggest improvements to data processes and methodologies for enhanced efficiency.
Core skills and knowledge:
- Proficiency in data visualisation software (eg Tableau, Power BI).
- Able to change Data Models (eg Tabular Models, Semantic Models) and use them for reporting.
- Domain knowledge on double‑entry accounting, finance systems change, Basel III/IV, CRR II, IFRS 9, credit risk lifecycle, capital and regulatory reporting.
- Proficiency in data analysis and manipulation using SQL, stored procedures, and OLAP cubes.
- Experience with ETL processes within on-prem data warehouses, SSIS ETL packages, and ETL in cloud-based Medallion architecture solutions.
- Strong analytical and problem-solving skills with attention to detail. Excellent communication skills, both verbal and written, with the ability to present complex information clearly.
- Knowledge of programming languages such as Python is advantageous.
